Face recognition systems are progressively becoming popular as means of extracting biometric information. Face recognition has a critical role in biometric systems and is attractive for numerous applications including visual surveillance and security. Because of the general public acceptance of face images on various documents, face recognition has a great potential to become the next generation biometric technology of choice. Face images are also the only biometric information available in some legacy databases and international terrorist watch-lists and can be acquired even without subjects' cooperation.

Though there has been a great deal of progress in face detection and recognition in the last few years, many problems remain unsolved. Research on face detection must confront with many challenging problems, especially when dealing with outdoor illumination, pose variation with large rotation angles, low image quality, low resolution, occlusion, and background changes in complex real-life scenes. The design of face recognition algorithms that are effective over a wide range of viewpoints, complex outdoor lighting, occlusions, facial expressions, and aging of subjects, is still a major area of research. Before one claims that the facial image processing / analysis system is reliable, rigorous testing and verification on real-world datasets must be performed, including databases for face analysis and tracking in digital video. 3D head model assisted recognition is another research area where new solutions are urgently needed to enhance robustness of today's recognition systems and enable real-time, face-oriented processing and analysis of visual data. Thus, vigorous research is needed to solve such outstanding challenging problems and propose advanced solutions and systems for emerging applications of facial image processing and analysis.

This special issue is particularly interested in recent progress in face detection and recognition that explores emerging themes such as digital video, 3D, near infrared, occlusion and disguise, long-term aging, and/or the lack of sufficient training data. Submitted articles must not have been previously published and must not be currently submitted for publication elsewhere. Topics of interest include, but are not limited to, the following: